Proceeding of the Electrical Engineering Computer Science and Informatics
Vol 2: EECSI 2015

Decision Support System for Heart Disease Diagnosing Using K-NN Algorithm

Yuwono, Tito ( Islamic University of Indonesia)
Setiawan, Noor Akhmad ( Gadjah Mada University)
Nugroho, Hanung Adi ( Gadjah Mada University)
Persada, Anugrah Galang ( Gadjah Mada University)
Prasojo, Ipin ( Islamic University of Indonesia)
Dewi, Sri Kusuma ( Islamic University of Indonesia)
Rahmadi, Ridho ( Islamic University of Indonesia)

Article Info

Publish Date
15 Aug 2015

Abstract

Heart disease is a notoriously dangerous disease which possibly causing the death. An electrocardiogram (ECG) is used for a diagnosis of the disease. It is often, however, a fault diagnosis by a doctor misleads to inappropriate treatment, which increases a risk of death. This present work implements k-nearest neighbor (K-NN) on ECG data to get a better interpretation which expected to help a decision making in the diagnosis. For experiment, we use an ECG data from MIT BIH and zoom in on classification of three classes; normal, myocardial infarction and others. We use a single decision threshold to evaluate the validity of the experiment. The result shows an accuracy up to 87% with a value of K = 4.

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Journal Info
Proceeding of the Electrical Engineering Computer Science and Informatics
Website

Abbrev

EECSI

Publisher

IAES Indonesia Section and Partners

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, ...